Many computer-based applications and/or services have a need to distinguish between human and computer users (often referred to as “bots”) that access computer-accessible resources. For example, there are many online email services that allow a user to create email accounts by entering certain basic information. The user is then able to use the email accounts to send and receive emails. This ease of establishing email accounts has allowed spammers to use bots (e.g., computer programs) that automatically create email accounts with randomly generated account information, and employ the email accounts to send out thousands of spam emails. Other exemplary computer-based applications or services provide users with convenient ways to order goods or services, and are vulnerable to security and/or privacy breaches resulting from bots posing as human users.
User tests (sometimes known as Completely Automated Public Turing tests to tell Computers and Humans Apart (“CAPTCHA”), and also generically referred to as human interactive proofs (“HIPs”)) may be employed to distinguish between humans and bots. When a HIP is employed, a user is allowed to access certain resources only after passing a test based on the HIP that indicates that the user is human. Generally, HIPs are designed in a manner that bots have difficulty passing the tests, but humans find it easier to pass the tests.
Bots have become better at circumventing known text- and image-based HIPs through improved character recognition and image filtering and processing techniques. In some cases, a bot will pass HIP tests at a rate that may not be acceptable to computer-based services or applications or their users. There is a continuing need to develop HIPs that are useful to reliably differentiate human and non-human users.